## Complete Calibration and Detection Procedure

### Step 1: Setup Configuration Files

1. Create `arena_config.yml` with fixed marker positions:
    ```yaml
    markers:
      - id: 1
        position: [0, 0]
      - id: 2
        position: [0, 1]
      - id: 3
        position: [0, 2]
    ```

2. Create `arena_transformation.yml` with an initial transformation matrix (example identity matrix):
    ```yaml
    transformation_matrix: !!opencv-matrix
       rows: 3
       cols: 3
       dt: d
       data: [1, 0, 0, 0, 1, 0, 0, 0, 1]
    ```

### Step 2: Calibrate the Camera

1. Run the `calibration_webcam` node to capture frames and calibrate the camera:
    ```bash
    rosrun your_package calibration_webcam
    ```

2. Follow the on-screen instructions to capture at least 10 frames of the chessboard pattern from different angles and positions.

3. The calibration parameters will be saved to `camera_parameters.yml`.

### Step 3: Calibrate the Arena

1. Run the `arena_calibration` node to detect ArUco markers and calibrate the arena:
    ```bash
    rosrun your_package arena_calibration
    ```

2. The detected marker positions and transformation matrix will be saved to `arena_config.yml` and `arena_transformation.yml` respectively.

### Step 4: Run the Main Node

1. Run the `aruco_detector` node to detect ArUco markers and display their positions in the arena:
    ```bash
    rosrun your_package aruco_detector
    ```

2. The node will process frames from the camera, detect ArUco markers, and display their positions in the arena frame.